Face Generation

In this project, you'll use generative adversarial networks to generate new images of faces.

Get the Data

You'll be using two datasets in this project:

  • MNIST
  • CelebA

Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.

If you're using FloydHub, set data_dir to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".

In [1]:
data_dir = './data'

# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'


"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper

helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
Found mnist Data
Found celeba Data

Explore the Data

MNIST

As you're aware, the MNIST dataset contains images of handwritten digits. You can view the first number of examples by changing show_n_images.

In [2]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot

mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
Out[2]:
<matplotlib.image.AxesImage at 0x7f42078a4a20>

CelebA

The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images.

In [3]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Out[3]:
<matplotlib.image.AxesImage at 0x7f42077d2940>

Preprocess the Data

Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

The MNIST images are black and white images with a single color channel while the CelebA images have 3 color channels (RGB color channel).

Build the Neural Network

You'll build the components necessary to build a GANs by implementing the following functions below:

  • model_inputs
  • discriminator
  • generator
  • model_loss
  • model_opt
  • train

Check the Version of TensorFlow and Access to GPU

This will check to make sure you have the correct version of TensorFlow and access to a GPU

In [4]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf

# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer.  You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))

# Check for a GPU
if not tf.test.gpu_device_name():
    warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
    print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
TensorFlow Version: 1.0.1
Default GPU Device: /gpu:0

Input

Implement the model_inputs function to create TF Placeholders for the Neural Network. It should create the following placeholders:

  • Real input images placeholder with rank 4 using image_width, image_height, and image_channels.
  • Z input placeholder with rank 2 using z_dim.
  • Learning rate placeholder with rank 0.

Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)

In [5]:
import problem_unittests as tests

def model_inputs(image_width, image_height, image_channels, z_dim):
    """
    Create the model inputs
    :param image_width: The input image width
    :param image_height: The input image height
    :param image_channels: The number of image channels
    :param z_dim: The dimension of Z
    :return: Tuple of (tensor of real input images, tensor of z data, learning rate)
    """
    # TODO: Implement Function
    inputs_real = tf.placeholder(tf.float32, (None, image_width,image_height,image_channels), name='input_real') 
    inputs_z = tf.placeholder(tf.float32, (None, z_dim), name='input_z')
    learning_rate = tf.placeholder(tf.float32, name="learning_rate")

    return inputs_real, inputs_z, learning_rate


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
Tests Passed

Discriminator

Implement discriminator to create a discriminator neural network that discriminates on images. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the discriminator, tensor logits of the discriminator).

In [6]:
def discriminator(images, reuse=False):
    """
    Create the discriminator network
    :param images: Tensor of input image(s)
    :param reuse: Boolean if the weights should be reused
    :return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
    """
    # TODO: Implement Function
    alpha = 0.2
    with tf.variable_scope('discriminator', reuse=reuse): 
        # Input layer 28x28x*
        x1 = tf.layers.conv2d(images, 64, 5, strides=2, padding='same')
        relu1 = tf.maximum(alpha * x1, x1)
        # 14x14x64
        
        x2 = tf.layers.conv2d(relu1, 128, 5, strides=2, padding='same')
        bn2 = tf.layers.batch_normalization(x2, training=True)
        relu2 = tf.maximum(alpha * bn2, bn2)
        # 7x7x128

        # Flatten it
        flat = tf.reshape(relu2, (-1, 7*7*128))
        logits = tf.layers.dense(flat, 1)
        out = tf.sigmoid(logits)
        
        return out, logits


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Tests Passed

Generator

Implement generator to generate an image using z. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim images.

In [7]:
def generator(z, out_channel_dim, is_train=True):
    """
    Create the generator network
    :param z: Input z
    :param out_channel_dim: The number of channels in the output image
    :param is_train: Boolean if generator is being used for training
    :return: The tensor output of the generator
    """
    # TODO: Implement Function
    alpha = 0.2
    reuse = False if is_train==True else True
    with tf.variable_scope('generator', reuse=reuse):  
        x1 = tf.layers.dense(z, 7*7*256)
        x1 = tf.reshape(x1, (-1, 7, 7, 256))
        x1 = tf.layers.batch_normalization(x1, training=is_train)
        x1 = tf.maximum(alpha * x1, x1)
        # 7x7x256 now
        
        x2 = tf.layers.conv2d_transpose(x1, 128, 5, strides=2, padding='same')
        x2 = tf.layers.batch_normalization(x2, training=is_train)
        x2 = tf.maximum(alpha * x2, x2)
        # 14x14x128 now
        
        # Output layer
        logits = tf.layers.conv2d_transpose(x2, out_channel_dim, 5, strides=2, padding='same')
        # out_channel_dim now
        
        out = tf.tanh(logits)
    
    
    return out


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Tests Passed

Loss

Implement model_loss to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:

  • discriminator(images, reuse=False)
  • generator(z, out_channel_dim, is_train=True)
In [8]:
def model_loss(input_real, input_z, out_channel_dim):
    """
    Get the loss for the discriminator and generator
    :param input_real: Images from the real dataset
    :param input_z: Z input
    :param out_channel_dim: The number of channels in the output image
    :return: A tuple of (discriminator loss, generator loss)
    """
    # TODO: Implement Function
    g_model = generator(input_z, out_channel_dim, is_train=True)
    d_model_real, d_logits_real = discriminator(input_real)
    d_model_fake, d_logits_fake = discriminator(g_model, reuse=True)
    
    d_loss_real = tf.reduce_mean(
                  tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real, 
                                                          labels=tf.ones_like(d_logits_real) * (1 - 0.1)))
    d_loss_fake = tf.reduce_mean(
                  tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, 
                                                          labels=tf.zeros_like(d_logits_real)))
    d_loss = d_loss_real + d_loss_fake
    g_loss = tf.reduce_mean(
             tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake,
                                                     labels=tf.ones_like(d_logits_fake)))
    
    
    return d_loss, g_loss


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Tests Passed

Optimization

Implement model_opt to create the optimization operations for the GANs. Use tf.trainable_variables to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).

In [9]:
def model_opt(d_loss, g_loss, learning_rate, beta1):
    """
    Get optimization operations
    :param d_loss: Discriminator loss Tensor
    :param g_loss: Generator loss Tensor
    :param learning_rate: Learning Rate Placeholder
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :return: A tuple of (discriminator training operation, generator training operation)
    """
    # TODO: Implement Function
    t_vars = tf.trainable_variables()
    g_vars = [var for var in t_vars if var.name.startswith('generator')]
    d_vars = [var for var in t_vars if var.name.startswith('discriminator')]

    with tf.control_dependencies(tf.get_collection(tf.GraphKeys.UPDATE_OPS)):
        d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1).minimize(d_loss, var_list=d_vars)
        g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1).minimize(g_loss, var_list=g_vars)
    
    return d_train_opt, g_train_opt


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
Tests Passed

Neural Network Training

Show Output

Use this function to show the current output of the generator during training. It will help you determine how well the GANs is training.

In [10]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np

def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
    """
    Show example output for the generator
    :param sess: TensorFlow session
    :param n_images: Number of Images to display
    :param input_z: Input Z Tensor
    :param out_channel_dim: The number of channels in the output image
    :param image_mode: The mode to use for images ("RGB" or "L")
    """
    cmap = None if image_mode == 'RGB' else 'gray'
    z_dim = input_z.get_shape().as_list()[-1]
    example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])

    samples = sess.run(
        generator(input_z, out_channel_dim, False),
        feed_dict={input_z: example_z})

    images_grid = helper.images_square_grid(samples, image_mode)
    pyplot.imshow(images_grid, cmap=cmap)
    pyplot.show()

Train

Implement train to build and train the GANs. Use the following functions you implemented:

  • model_inputs(image_width, image_height, image_channels, z_dim)
  • model_loss(input_real, input_z, out_channel_dim)
  • model_opt(d_loss, g_loss, learning_rate, beta1)

Use the show_generator_output to show generator output while you train. Running show_generator_output for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator output every 100 batches.

In [11]:
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
    """
    Train the GAN
    :param epoch_count: Number of epochs
    :param batch_size: Batch Size
    :param z_dim: Z dimension
    :param learning_rate: Learning Rate
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :param get_batches: Function to get batches
    :param data_shape: Shape of the data
    :param data_image_mode: The image mode to use for images ("RGB" or "L")
    """
    # TODO: Build Model
    print(data_shape)
    input_real, input_z, lr = model_inputs(data_shape[1], data_shape[2], data_shape[3], z_dim)
    #input_real, input_z, lr = model_inputs(28, 28, 1, z_dim)
    channels = 3 if data_image_mode == 'RGB' else 1
    d_loss, g_loss = model_loss(input_real, input_z, channels)
    d_opt, g_opt = model_opt(d_loss, g_loss, lr, beta1)
    
    steps = 0
    show_every = 100
    print_every = 10
    with tf.Session() as sess:
        sess.run(tf.global_variables_initializer())
        for epoch_i in range(epoch_count):
            for batch_images in get_batches(batch_size):
                # TODO: Train Model
                #print(batch_images.shape)
                steps += 1
                batch_images *= 2
                batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))
                _ = sess.run(d_opt, feed_dict={input_real: batch_images, input_z: batch_z, lr: learning_rate})
                _ = sess.run(g_opt, feed_dict={input_z: batch_z, input_real: batch_images, lr: learning_rate})
                _ = sess.run(g_opt, feed_dict={input_z: batch_z, input_real: batch_images, lr: learning_rate})
                
                if steps % print_every == 0:
                    train_loss_d = sess.run(d_loss, {input_z: batch_z, input_real: batch_images})
                    train_loss_g = g_loss.eval({input_z: batch_z, input_real: batch_images})
                
                    print("Epoch {}/{}...".format(epoch_i+1, epoch_count),
              "Discriminator Loss: {:.4f}...".format(train_loss_d),
              "Generator Loss: {:.4f}".format(train_loss_g))  
                
                if steps % show_every == 0:
                   show_generator_output(sess, 20, input_z, channels, data_image_mode) 
        
                
                

MNIST

Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.

In [12]:
batch_size = 32
z_dim = 100
learning_rate = 0.0002
beta1 = 0.5


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2

mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
          mnist_dataset.shape, mnist_dataset.image_mode)
(60000, 28, 28, 1)
Epoch 1/2... Discriminator Loss: 4.0147... Generator Loss: 0.0344
Epoch 1/2... Discriminator Loss: 3.1309... Generator Loss: 0.1024
Epoch 1/2... Discriminator Loss: 2.4692... Generator Loss: 0.2618
Epoch 1/2... Discriminator Loss: 2.0308... Generator Loss: 0.3820
Epoch 1/2... Discriminator Loss: 2.0643... Generator Loss: 0.2839
Epoch 1/2... Discriminator Loss: 1.9508... Generator Loss: 0.3216
Epoch 1/2... Discriminator Loss: 1.8986... Generator Loss: 0.5210
Epoch 1/2... Discriminator Loss: 1.8184... Generator Loss: 0.4710
Epoch 1/2... Discriminator Loss: 1.7688... Generator Loss: 0.5730
Epoch 1/2... Discriminator Loss: 1.6837... Generator Loss: 0.5178
Epoch 1/2... Discriminator Loss: 1.6579... Generator Loss: 0.5690
Epoch 1/2... Discriminator Loss: 1.6787... Generator Loss: 0.5915
Epoch 1/2... Discriminator Loss: 1.6365... Generator Loss: 0.5651
Epoch 1/2... Discriminator Loss: 1.5708... Generator Loss: 0.5747
Epoch 1/2... Discriminator Loss: 1.5325... Generator Loss: 0.6853
Epoch 1/2... Discriminator Loss: 1.5328... Generator Loss: 0.6334
Epoch 1/2... Discriminator Loss: 1.5784... Generator Loss: 0.7351
Epoch 1/2... Discriminator Loss: 1.5344... Generator Loss: 0.5845
Epoch 1/2... Discriminator Loss: 1.5727... Generator Loss: 0.4756
Epoch 1/2... Discriminator Loss: 1.5889... Generator Loss: 0.5612
Epoch 1/2... Discriminator Loss: 1.4299... Generator Loss: 0.6395
Epoch 1/2... Discriminator Loss: 1.5247... Generator Loss: 0.5676
Epoch 1/2... Discriminator Loss: 1.4798... Generator Loss: 0.7852
Epoch 1/2... Discriminator Loss: 1.5006... Generator Loss: 0.5069
Epoch 1/2... Discriminator Loss: 1.4112... Generator Loss: 0.5581
Epoch 1/2... Discriminator Loss: 1.4831... Generator Loss: 0.6584
Epoch 1/2... Discriminator Loss: 1.3490... Generator Loss: 0.7629
Epoch 1/2... Discriminator Loss: 1.4382... Generator Loss: 0.7705
Epoch 1/2... Discriminator Loss: 1.4067... Generator Loss: 0.6236
Epoch 1/2... Discriminator Loss: 1.3407... Generator Loss: 0.6589
Epoch 1/2... Discriminator Loss: 1.4339... Generator Loss: 0.5440
Epoch 1/2... Discriminator Loss: 1.4147... Generator Loss: 0.8328
Epoch 1/2... Discriminator Loss: 1.4537... Generator Loss: 0.5416
Epoch 1/2... Discriminator Loss: 1.3644... Generator Loss: 0.7905
Epoch 1/2... Discriminator Loss: 1.4574... Generator Loss: 0.6011
Epoch 1/2... Discriminator Loss: 1.3431... Generator Loss: 0.6732
Epoch 1/2... Discriminator Loss: 1.2522... Generator Loss: 1.0624
Epoch 1/2... Discriminator Loss: 1.3587... Generator Loss: 0.8690
Epoch 1/2... Discriminator Loss: 1.4506... Generator Loss: 0.5074
Epoch 1/2... Discriminator Loss: 1.4115... Generator Loss: 0.6146
Epoch 1/2... Discriminator Loss: 1.4179... Generator Loss: 0.6336
Epoch 1/2... Discriminator Loss: 1.3760... Generator Loss: 0.6140
Epoch 1/2... Discriminator Loss: 1.3004... Generator Loss: 0.8885
Epoch 1/2... Discriminator Loss: 1.4468... Generator Loss: 0.6358
Epoch 1/2... Discriminator Loss: 1.3379... Generator Loss: 0.8217
Epoch 1/2... Discriminator Loss: 1.4229... Generator Loss: 0.7216
Epoch 1/2... Discriminator Loss: 1.6580... Generator Loss: 0.8007
Epoch 1/2... Discriminator Loss: 1.4308... Generator Loss: 0.7466
Epoch 1/2... Discriminator Loss: 1.4329... Generator Loss: 0.6153
Epoch 1/2... Discriminator Loss: 1.3630... Generator Loss: 0.8475
Epoch 1/2... Discriminator Loss: 1.4415... Generator Loss: 0.6021
Epoch 1/2... Discriminator Loss: 1.4302... Generator Loss: 0.7098
Epoch 1/2... Discriminator Loss: 1.3955... Generator Loss: 0.6859
Epoch 1/2... Discriminator Loss: 1.4580... Generator Loss: 0.6832
Epoch 1/2... Discriminator Loss: 1.3880... Generator Loss: 0.6870
Epoch 1/2... Discriminator Loss: 1.4004... Generator Loss: 0.6893
Epoch 1/2... Discriminator Loss: 1.3740... Generator Loss: 0.8298
Epoch 1/2... Discriminator Loss: 1.5188... Generator Loss: 0.6968
Epoch 1/2... Discriminator Loss: 1.5549... Generator Loss: 0.5819
Epoch 1/2... Discriminator Loss: 1.5220... Generator Loss: 0.5952
Epoch 1/2... Discriminator Loss: 1.4369... Generator Loss: 0.6297
Epoch 1/2... Discriminator Loss: 1.4456... Generator Loss: 0.8200
Epoch 1/2... Discriminator Loss: 1.4113... Generator Loss: 0.8516
Epoch 1/2... Discriminator Loss: 1.5680... Generator Loss: 0.5949
Epoch 1/2... Discriminator Loss: 1.5988... Generator Loss: 0.5658
Epoch 1/2... Discriminator Loss: 1.3413... Generator Loss: 0.7833
Epoch 1/2... Discriminator Loss: 1.4289... Generator Loss: 0.6067
Epoch 1/2... Discriminator Loss: 1.5149... Generator Loss: 0.6136
Epoch 1/2... Discriminator Loss: 1.5213... Generator Loss: 0.7066
Epoch 1/2... Discriminator Loss: 1.4251... Generator Loss: 0.6561
Epoch 1/2... Discriminator Loss: 1.3988... Generator Loss: 0.8101
Epoch 1/2... Discriminator Loss: 1.4243... Generator Loss: 0.6820
Epoch 1/2... Discriminator Loss: 1.5999... Generator Loss: 0.4255
Epoch 1/2... Discriminator Loss: 1.5046... Generator Loss: 0.5948
Epoch 1/2... Discriminator Loss: 1.4674... Generator Loss: 0.6645
Epoch 1/2... Discriminator Loss: 1.3855... Generator Loss: 0.7032
Epoch 1/2... Discriminator Loss: 1.4776... Generator Loss: 0.6551
Epoch 1/2... Discriminator Loss: 1.3563... Generator Loss: 0.8549
Epoch 1/2... Discriminator Loss: 1.4230... Generator Loss: 0.8299
Epoch 1/2... Discriminator Loss: 1.3537... Generator Loss: 0.7390
Epoch 1/2... Discriminator Loss: 1.4087... Generator Loss: 0.6068
Epoch 1/2... Discriminator Loss: 1.3027... Generator Loss: 1.0703
Epoch 1/2... Discriminator Loss: 1.4882... Generator Loss: 0.5161
Epoch 1/2... Discriminator Loss: 1.4284... Generator Loss: 0.6043
Epoch 1/2... Discriminator Loss: 1.3799... Generator Loss: 0.7313
Epoch 1/2... Discriminator Loss: 1.4513... Generator Loss: 0.5406
Epoch 1/2... Discriminator Loss: 1.3828... Generator Loss: 0.6218
Epoch 1/2... Discriminator Loss: 1.3661... Generator Loss: 0.7103
Epoch 1/2... Discriminator Loss: 1.5041... Generator Loss: 0.6370
Epoch 1/2... Discriminator Loss: 1.3110... Generator Loss: 0.7206
Epoch 1/2... Discriminator Loss: 1.4531... Generator Loss: 0.6527
Epoch 1/2... Discriminator Loss: 1.3708... Generator Loss: 0.7775
Epoch 1/2... Discriminator Loss: 1.4997... Generator Loss: 0.5024
Epoch 1/2... Discriminator Loss: 1.3429... Generator Loss: 0.7017
Epoch 1/2... Discriminator Loss: 1.3540... Generator Loss: 0.7465
Epoch 1/2... Discriminator Loss: 1.3750... Generator Loss: 0.6411
Epoch 1/2... Discriminator Loss: 1.3920... Generator Loss: 0.8302
Epoch 1/2... Discriminator Loss: 1.4902... Generator Loss: 0.4709
Epoch 1/2... Discriminator Loss: 1.3408... Generator Loss: 0.6915
Epoch 1/2... Discriminator Loss: 1.4508... Generator Loss: 0.5970
Epoch 1/2... Discriminator Loss: 1.4523... Generator Loss: 0.6596
Epoch 1/2... Discriminator Loss: 1.4890... Generator Loss: 0.4724
Epoch 1/2... Discriminator Loss: 1.4048... Generator Loss: 0.7842
Epoch 1/2... Discriminator Loss: 1.5109... Generator Loss: 0.6107
Epoch 1/2... Discriminator Loss: 1.4297... Generator Loss: 0.6964
Epoch 1/2... Discriminator Loss: 1.4579... Generator Loss: 0.7866
Epoch 1/2... Discriminator Loss: 1.4137... Generator Loss: 0.8320
Epoch 1/2... Discriminator Loss: 1.4676... Generator Loss: 0.5484
Epoch 1/2... Discriminator Loss: 1.4253... Generator Loss: 0.6050
Epoch 1/2... Discriminator Loss: 1.5332... Generator Loss: 0.4575
Epoch 1/2... Discriminator Loss: 1.3821... Generator Loss: 0.5820
Epoch 1/2... Discriminator Loss: 1.4612... Generator Loss: 0.5621
Epoch 1/2... Discriminator Loss: 1.3279... Generator Loss: 0.7860
Epoch 1/2... Discriminator Loss: 1.3214... Generator Loss: 0.7955
Epoch 1/2... Discriminator Loss: 1.4276... Generator Loss: 0.6037
Epoch 1/2... Discriminator Loss: 1.3799... Generator Loss: 0.7584
Epoch 1/2... Discriminator Loss: 1.3277... Generator Loss: 0.7841
Epoch 1/2... Discriminator Loss: 1.3149... Generator Loss: 0.6277
Epoch 1/2... Discriminator Loss: 1.4144... Generator Loss: 0.5788
Epoch 1/2... Discriminator Loss: 1.3861... Generator Loss: 0.7878
Epoch 1/2... Discriminator Loss: 1.3281... Generator Loss: 0.8422
Epoch 1/2... Discriminator Loss: 1.3901... Generator Loss: 0.7021
Epoch 1/2... Discriminator Loss: 1.4730... Generator Loss: 0.7597
Epoch 1/2... Discriminator Loss: 1.5638... Generator Loss: 0.4780
Epoch 1/2... Discriminator Loss: 1.3749... Generator Loss: 0.6815
Epoch 1/2... Discriminator Loss: 1.3765... Generator Loss: 0.5985
Epoch 1/2... Discriminator Loss: 1.3889... Generator Loss: 0.6780
Epoch 1/2... Discriminator Loss: 1.2554... Generator Loss: 0.8482
Epoch 1/2... Discriminator Loss: 1.2987... Generator Loss: 0.8834
Epoch 1/2... Discriminator Loss: 1.4782... Generator Loss: 0.5905
Epoch 1/2... Discriminator Loss: 1.4453... Generator Loss: 0.5702
Epoch 1/2... Discriminator Loss: 1.3839... Generator Loss: 0.7896
Epoch 1/2... Discriminator Loss: 1.2921... Generator Loss: 0.6445
Epoch 1/2... Discriminator Loss: 1.3271... Generator Loss: 0.7013
Epoch 1/2... Discriminator Loss: 1.5270... Generator Loss: 0.4712
Epoch 1/2... Discriminator Loss: 1.4299... Generator Loss: 0.6882
Epoch 1/2... Discriminator Loss: 1.4488... Generator Loss: 0.5168
Epoch 1/2... Discriminator Loss: 1.2476... Generator Loss: 0.8800
Epoch 1/2... Discriminator Loss: 1.3060... Generator Loss: 0.6978
Epoch 1/2... Discriminator Loss: 1.2893... Generator Loss: 0.7932
Epoch 1/2... Discriminator Loss: 1.2884... Generator Loss: 0.7012
Epoch 1/2... Discriminator Loss: 1.3104... Generator Loss: 0.6958
Epoch 1/2... Discriminator Loss: 1.2752... Generator Loss: 0.7505
Epoch 1/2... Discriminator Loss: 1.3218... Generator Loss: 0.9685
Epoch 1/2... Discriminator Loss: 1.4202... Generator Loss: 0.5313
Epoch 1/2... Discriminator Loss: 1.3370... Generator Loss: 0.7393
Epoch 1/2... Discriminator Loss: 1.3017... Generator Loss: 0.7569
Epoch 1/2... Discriminator Loss: 1.3428... Generator Loss: 1.2086
Epoch 1/2... Discriminator Loss: 1.3670... Generator Loss: 0.6750
Epoch 1/2... Discriminator Loss: 1.2936... Generator Loss: 0.6289
Epoch 1/2... Discriminator Loss: 1.2925... Generator Loss: 0.9509
Epoch 1/2... Discriminator Loss: 1.3659... Generator Loss: 0.7476
Epoch 1/2... Discriminator Loss: 1.3514... Generator Loss: 0.6209
Epoch 1/2... Discriminator Loss: 1.2578... Generator Loss: 0.7395
Epoch 1/2... Discriminator Loss: 1.4146... Generator Loss: 1.1347
Epoch 1/2... Discriminator Loss: 1.4205... Generator Loss: 0.5510
Epoch 1/2... Discriminator Loss: 1.3869... Generator Loss: 0.5661
Epoch 1/2... Discriminator Loss: 1.2986... Generator Loss: 0.8894
Epoch 1/2... Discriminator Loss: 1.3418... Generator Loss: 0.6340
Epoch 1/2... Discriminator Loss: 1.4575... Generator Loss: 0.4986
Epoch 1/2... Discriminator Loss: 1.2735... Generator Loss: 0.6846
Epoch 1/2... Discriminator Loss: 1.7695... Generator Loss: 0.2999
Epoch 1/2... Discriminator Loss: 1.2191... Generator Loss: 1.0760
Epoch 1/2... Discriminator Loss: 1.2174... Generator Loss: 0.9262
Epoch 1/2... Discriminator Loss: 1.4870... Generator Loss: 0.4496
Epoch 1/2... Discriminator Loss: 1.2266... Generator Loss: 0.7571
Epoch 1/2... Discriminator Loss: 1.2802... Generator Loss: 0.7040
Epoch 1/2... Discriminator Loss: 1.3053... Generator Loss: 0.6020
Epoch 1/2... Discriminator Loss: 1.3955... Generator Loss: 0.6657
Epoch 1/2... Discriminator Loss: 1.3114... Generator Loss: 1.0193
Epoch 1/2... Discriminator Loss: 1.2989... Generator Loss: 0.8621
Epoch 1/2... Discriminator Loss: 1.3058... Generator Loss: 0.6271
Epoch 1/2... Discriminator Loss: 1.3259... Generator Loss: 0.6906
Epoch 1/2... Discriminator Loss: 1.4039... Generator Loss: 0.6285
Epoch 1/2... Discriminator Loss: 1.3180... Generator Loss: 0.7032
Epoch 1/2... Discriminator Loss: 1.6312... Generator Loss: 0.3628
Epoch 1/2... Discriminator Loss: 1.2306... Generator Loss: 0.7349
Epoch 1/2... Discriminator Loss: 1.4606... Generator Loss: 0.5046
Epoch 1/2... Discriminator Loss: 1.5273... Generator Loss: 0.4565
Epoch 1/2... Discriminator Loss: 1.3119... Generator Loss: 0.6499
Epoch 1/2... Discriminator Loss: 1.0997... Generator Loss: 1.2824
Epoch 1/2... Discriminator Loss: 1.1900... Generator Loss: 0.7661
Epoch 1/2... Discriminator Loss: 1.1477... Generator Loss: 0.7931
Epoch 1/2... Discriminator Loss: 1.3418... Generator Loss: 0.6713
Epoch 1/2... Discriminator Loss: 1.2727... Generator Loss: 0.6502
Epoch 1/2... Discriminator Loss: 1.5289... Generator Loss: 0.4714
Epoch 1/2... Discriminator Loss: 1.3987... Generator Loss: 0.5066
Epoch 2/2... Discriminator Loss: 1.3226... Generator Loss: 0.5992
Epoch 2/2... Discriminator Loss: 1.3963... Generator Loss: 0.6251
Epoch 2/2... Discriminator Loss: 1.2846... Generator Loss: 0.6725
Epoch 2/2... Discriminator Loss: 1.3645... Generator Loss: 1.0176
Epoch 2/2... Discriminator Loss: 1.3613... Generator Loss: 0.5467
Epoch 2/2... Discriminator Loss: 1.4370... Generator Loss: 0.4524
Epoch 2/2... Discriminator Loss: 1.3063... Generator Loss: 0.6915
Epoch 2/2... Discriminator Loss: 1.1113... Generator Loss: 0.8651
Epoch 2/2... Discriminator Loss: 1.2890... Generator Loss: 0.8291
Epoch 2/2... Discriminator Loss: 1.2249... Generator Loss: 0.7181
Epoch 2/2... Discriminator Loss: 1.2840... Generator Loss: 0.6916
Epoch 2/2... Discriminator Loss: 1.3379... Generator Loss: 0.6525
Epoch 2/2... Discriminator Loss: 1.3091... Generator Loss: 1.2008
Epoch 2/2... Discriminator Loss: 1.2487... Generator Loss: 0.6922
Epoch 2/2... Discriminator Loss: 1.4323... Generator Loss: 0.4686
Epoch 2/2... Discriminator Loss: 2.7097... Generator Loss: 2.2824
Epoch 2/2... Discriminator Loss: 1.1852... Generator Loss: 0.9703
Epoch 2/2... Discriminator Loss: 1.2978... Generator Loss: 0.6047
Epoch 2/2... Discriminator Loss: 1.2868... Generator Loss: 0.6593
Epoch 2/2... Discriminator Loss: 1.1870... Generator Loss: 0.7442
Epoch 2/2... Discriminator Loss: 1.3811... Generator Loss: 0.5245
Epoch 2/2... Discriminator Loss: 1.3472... Generator Loss: 0.6298
Epoch 2/2... Discriminator Loss: 1.5293... Generator Loss: 0.3997
Epoch 2/2... Discriminator Loss: 1.1632... Generator Loss: 1.1296
Epoch 2/2... Discriminator Loss: 1.1273... Generator Loss: 0.9016
Epoch 2/2... Discriminator Loss: 1.2649... Generator Loss: 0.8858
Epoch 2/2... Discriminator Loss: 1.3147... Generator Loss: 0.5589
Epoch 2/2... Discriminator Loss: 1.3752... Generator Loss: 0.5462
Epoch 2/2... Discriminator Loss: 1.2573... Generator Loss: 0.7120
Epoch 2/2... Discriminator Loss: 1.0998... Generator Loss: 0.8315
Epoch 2/2... Discriminator Loss: 1.4632... Generator Loss: 0.4594
Epoch 2/2... Discriminator Loss: 1.3247... Generator Loss: 0.6072
Epoch 2/2... Discriminator Loss: 1.2550... Generator Loss: 0.7747
Epoch 2/2... Discriminator Loss: 1.3035... Generator Loss: 0.6534
Epoch 2/2... Discriminator Loss: 1.2096... Generator Loss: 0.7063
Epoch 2/2... Discriminator Loss: 1.4217... Generator Loss: 0.4722
Epoch 2/2... Discriminator Loss: 1.2616... Generator Loss: 0.6378
Epoch 2/2... Discriminator Loss: 1.1760... Generator Loss: 0.8175
Epoch 2/2... Discriminator Loss: 1.2313... Generator Loss: 0.6440
Epoch 2/2... Discriminator Loss: 1.6458... Generator Loss: 0.3370
Epoch 2/2... Discriminator Loss: 1.7354... Generator Loss: 0.3252
Epoch 2/2... Discriminator Loss: 1.1705... Generator Loss: 0.9961
Epoch 2/2... Discriminator Loss: 1.2055... Generator Loss: 0.7269
Epoch 2/2... Discriminator Loss: 1.2768... Generator Loss: 0.6384
Epoch 2/2... Discriminator Loss: 1.4457... Generator Loss: 0.4733
Epoch 2/2... Discriminator Loss: 1.2018... Generator Loss: 0.8739
Epoch 2/2... Discriminator Loss: 1.1081... Generator Loss: 0.9492
Epoch 2/2... Discriminator Loss: 1.1001... Generator Loss: 0.9308
Epoch 2/2... Discriminator Loss: 1.1948... Generator Loss: 1.0680
Epoch 2/2... Discriminator Loss: 1.1299... Generator Loss: 0.8074
Epoch 2/2... Discriminator Loss: 1.2411... Generator Loss: 0.6606
Epoch 2/2... Discriminator Loss: 1.0885... Generator Loss: 0.9131
Epoch 2/2... Discriminator Loss: 1.1657... Generator Loss: 0.7696
Epoch 2/2... Discriminator Loss: 1.1482... Generator Loss: 0.9419
Epoch 2/2... Discriminator Loss: 1.1293... Generator Loss: 0.8952
Epoch 2/2... Discriminator Loss: 1.4113... Generator Loss: 0.4815
Epoch 2/2... Discriminator Loss: 1.5753... Generator Loss: 0.3826
Epoch 2/2... Discriminator Loss: 1.0691... Generator Loss: 1.1081
Epoch 2/2... Discriminator Loss: 1.0976... Generator Loss: 0.8306
Epoch 2/2... Discriminator Loss: 1.2188... Generator Loss: 0.9540
Epoch 2/2... Discriminator Loss: 1.3167... Generator Loss: 0.5961
Epoch 2/2... Discriminator Loss: 1.2657... Generator Loss: 0.6188
Epoch 2/2... Discriminator Loss: 2.0278... Generator Loss: 0.2305
Epoch 2/2... Discriminator Loss: 1.2979... Generator Loss: 0.8698
Epoch 2/2... Discriminator Loss: 1.2992... Generator Loss: 0.5802
Epoch 2/2... Discriminator Loss: 1.1623... Generator Loss: 0.8088
Epoch 2/2... Discriminator Loss: 1.2879... Generator Loss: 0.5986
Epoch 2/2... Discriminator Loss: 1.2044... Generator Loss: 0.8898
Epoch 2/2... Discriminator Loss: 1.3747... Generator Loss: 0.5907
Epoch 2/2... Discriminator Loss: 1.3706... Generator Loss: 0.4997
Epoch 2/2... Discriminator Loss: 1.1589... Generator Loss: 1.2214
Epoch 2/2... Discriminator Loss: 1.4452... Generator Loss: 0.4325
Epoch 2/2... Discriminator Loss: 1.0668... Generator Loss: 1.0929
Epoch 2/2... Discriminator Loss: 1.2539... Generator Loss: 0.6100
Epoch 2/2... Discriminator Loss: 2.2283... Generator Loss: 0.1876
Epoch 2/2... Discriminator Loss: 1.3798... Generator Loss: 0.9157
Epoch 2/2... Discriminator Loss: 1.1909... Generator Loss: 0.7174
Epoch 2/2... Discriminator Loss: 1.0624... Generator Loss: 0.7688
Epoch 2/2... Discriminator Loss: 1.2484... Generator Loss: 0.6448
Epoch 2/2... Discriminator Loss: 1.0582... Generator Loss: 0.8562
Epoch 2/2... Discriminator Loss: 1.0759... Generator Loss: 0.9230
Epoch 2/2... Discriminator Loss: 1.1083... Generator Loss: 1.0588
Epoch 2/2... Discriminator Loss: 1.2985... Generator Loss: 1.1770
Epoch 2/2... Discriminator Loss: 1.0996... Generator Loss: 0.7679
Epoch 2/2... Discriminator Loss: 1.2289... Generator Loss: 0.7723
Epoch 2/2... Discriminator Loss: 1.3933... Generator Loss: 0.5160
Epoch 2/2... Discriminator Loss: 1.5620... Generator Loss: 0.3889
Epoch 2/2... Discriminator Loss: 1.2936... Generator Loss: 0.6728
Epoch 2/2... Discriminator Loss: 1.2412... Generator Loss: 0.6386
Epoch 2/2... Discriminator Loss: 1.2607... Generator Loss: 0.6525
Epoch 2/2... Discriminator Loss: 1.2496... Generator Loss: 0.5915
Epoch 2/2... Discriminator Loss: 1.1650... Generator Loss: 1.2748
Epoch 2/2... Discriminator Loss: 1.0915... Generator Loss: 1.1231
Epoch 2/2... Discriminator Loss: 1.3326... Generator Loss: 0.5329
Epoch 2/2... Discriminator Loss: 1.4447... Generator Loss: 0.4488
Epoch 2/2... Discriminator Loss: 1.2489... Generator Loss: 0.6543
Epoch 2/2... Discriminator Loss: 1.1613... Generator Loss: 0.7667
Epoch 2/2... Discriminator Loss: 1.0981... Generator Loss: 0.8992
Epoch 2/2... Discriminator Loss: 1.2322... Generator Loss: 0.6138
Epoch 2/2... Discriminator Loss: 1.0952... Generator Loss: 0.9437
Epoch 2/2... Discriminator Loss: 1.3487... Generator Loss: 0.5134
Epoch 2/2... Discriminator Loss: 1.1015... Generator Loss: 1.0542
Epoch 2/2... Discriminator Loss: 1.0702... Generator Loss: 0.9015
Epoch 2/2... Discriminator Loss: 1.2298... Generator Loss: 0.6205
Epoch 2/2... Discriminator Loss: 0.9425... Generator Loss: 1.3143
Epoch 2/2... Discriminator Loss: 1.3151... Generator Loss: 0.5794
Epoch 2/2... Discriminator Loss: 1.1692... Generator Loss: 0.9637
Epoch 2/2... Discriminator Loss: 1.1969... Generator Loss: 0.6874
Epoch 2/2... Discriminator Loss: 1.1247... Generator Loss: 0.8983
Epoch 2/2... Discriminator Loss: 1.0669... Generator Loss: 0.9809
Epoch 2/2... Discriminator Loss: 1.1784... Generator Loss: 0.9618
Epoch 2/2... Discriminator Loss: 1.1202... Generator Loss: 1.0871
Epoch 2/2... Discriminator Loss: 2.1806... Generator Loss: 1.1267
Epoch 2/2... Discriminator Loss: 1.3769... Generator Loss: 0.6302
Epoch 2/2... Discriminator Loss: 1.3286... Generator Loss: 0.5835
Epoch 2/2... Discriminator Loss: 1.1900... Generator Loss: 0.8919
Epoch 2/2... Discriminator Loss: 1.0233... Generator Loss: 0.9727
Epoch 2/2... Discriminator Loss: 1.0332... Generator Loss: 1.1479
Epoch 2/2... Discriminator Loss: 1.3924... Generator Loss: 0.5144
Epoch 2/2... Discriminator Loss: 1.0133... Generator Loss: 1.0534
Epoch 2/2... Discriminator Loss: 1.1345... Generator Loss: 0.7293
Epoch 2/2... Discriminator Loss: 1.4066... Generator Loss: 0.4883
Epoch 2/2... Discriminator Loss: 1.1039... Generator Loss: 0.8567
Epoch 2/2... Discriminator Loss: 1.0297... Generator Loss: 0.9034
Epoch 2/2... Discriminator Loss: 1.1803... Generator Loss: 0.7142
Epoch 2/2... Discriminator Loss: 1.0068... Generator Loss: 1.0348
Epoch 2/2... Discriminator Loss: 1.1694... Generator Loss: 1.3359
Epoch 2/2... Discriminator Loss: 1.2283... Generator Loss: 0.9358
Epoch 2/2... Discriminator Loss: 1.1210... Generator Loss: 0.8712
Epoch 2/2... Discriminator Loss: 1.3227... Generator Loss: 0.5745
Epoch 2/2... Discriminator Loss: 1.2616... Generator Loss: 0.5929
Epoch 2/2... Discriminator Loss: 1.0877... Generator Loss: 0.8512
Epoch 2/2... Discriminator Loss: 1.2745... Generator Loss: 0.7556
Epoch 2/2... Discriminator Loss: 1.2804... Generator Loss: 0.5982
Epoch 2/2... Discriminator Loss: 1.1994... Generator Loss: 0.7779
Epoch 2/2... Discriminator Loss: 1.5273... Generator Loss: 0.4781
Epoch 2/2... Discriminator Loss: 1.2346... Generator Loss: 0.6863
Epoch 2/2... Discriminator Loss: 1.0582... Generator Loss: 0.9170
Epoch 2/2... Discriminator Loss: 1.2672... Generator Loss: 0.6133
Epoch 2/2... Discriminator Loss: 1.0998... Generator Loss: 0.8705
Epoch 2/2... Discriminator Loss: 1.2278... Generator Loss: 0.6981
Epoch 2/2... Discriminator Loss: 1.2353... Generator Loss: 0.7389
Epoch 2/2... Discriminator Loss: 1.4936... Generator Loss: 0.4408
Epoch 2/2... Discriminator Loss: 1.0767... Generator Loss: 1.0424
Epoch 2/2... Discriminator Loss: 1.1708... Generator Loss: 0.7250
Epoch 2/2... Discriminator Loss: 1.1235... Generator Loss: 0.7921
Epoch 2/2... Discriminator Loss: 1.1771... Generator Loss: 0.8789
Epoch 2/2... Discriminator Loss: 2.5846... Generator Loss: 2.6656
Epoch 2/2... Discriminator Loss: 1.1058... Generator Loss: 1.0355
Epoch 2/2... Discriminator Loss: 1.2731... Generator Loss: 0.6164
Epoch 2/2... Discriminator Loss: 1.1307... Generator Loss: 0.7153
Epoch 2/2... Discriminator Loss: 1.2479... Generator Loss: 0.6388
Epoch 2/2... Discriminator Loss: 1.0744... Generator Loss: 1.1691
Epoch 2/2... Discriminator Loss: 1.0272... Generator Loss: 1.0942
Epoch 2/2... Discriminator Loss: 1.1349... Generator Loss: 0.8237
Epoch 2/2... Discriminator Loss: 1.1931... Generator Loss: 0.6784
Epoch 2/2... Discriminator Loss: 1.1905... Generator Loss: 0.6399
Epoch 2/2... Discriminator Loss: 1.4014... Generator Loss: 0.5121
Epoch 2/2... Discriminator Loss: 1.2479... Generator Loss: 0.6317
Epoch 2/2... Discriminator Loss: 1.0507... Generator Loss: 0.9342
Epoch 2/2... Discriminator Loss: 1.2327... Generator Loss: 0.6116
Epoch 2/2... Discriminator Loss: 1.2213... Generator Loss: 0.7306
Epoch 2/2... Discriminator Loss: 1.2324... Generator Loss: 0.6509
Epoch 2/2... Discriminator Loss: 1.4939... Generator Loss: 0.4567
Epoch 2/2... Discriminator Loss: 1.1944... Generator Loss: 0.7997
Epoch 2/2... Discriminator Loss: 1.1637... Generator Loss: 0.7119
Epoch 2/2... Discriminator Loss: 1.2665... Generator Loss: 0.6480
Epoch 2/2... Discriminator Loss: 1.1813... Generator Loss: 0.7255
Epoch 2/2... Discriminator Loss: 1.0531... Generator Loss: 1.1170
Epoch 2/2... Discriminator Loss: 0.9808... Generator Loss: 1.0939
Epoch 2/2... Discriminator Loss: 1.4589... Generator Loss: 0.4705
Epoch 2/2... Discriminator Loss: 1.1517... Generator Loss: 0.8587
Epoch 2/2... Discriminator Loss: 1.3996... Generator Loss: 0.9838
Epoch 2/2... Discriminator Loss: 2.0392... Generator Loss: 0.3035
Epoch 2/2... Discriminator Loss: 1.2174... Generator Loss: 0.6878
Epoch 2/2... Discriminator Loss: 1.5416... Generator Loss: 0.4354
Epoch 2/2... Discriminator Loss: 1.2654... Generator Loss: 0.6789
Epoch 2/2... Discriminator Loss: 1.2573... Generator Loss: 0.6293
Epoch 2/2... Discriminator Loss: 1.2382... Generator Loss: 0.7419
Epoch 2/2... Discriminator Loss: 1.0271... Generator Loss: 0.9830
Epoch 2/2... Discriminator Loss: 1.2946... Generator Loss: 0.6428
Epoch 2/2... Discriminator Loss: 0.9785... Generator Loss: 1.0162
Epoch 2/2... Discriminator Loss: 1.2516... Generator Loss: 0.6478
Epoch 2/2... Discriminator Loss: 1.1538... Generator Loss: 0.7446
Epoch 2/2... Discriminator Loss: 1.2186... Generator Loss: 0.6375
Epoch 2/2... Discriminator Loss: 1.5382... Generator Loss: 1.0980
Epoch 2/2... Discriminator Loss: 1.0481... Generator Loss: 1.0104
Epoch 2/2... Discriminator Loss: 1.2926... Generator Loss: 0.6098

CelebA

Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.

In [13]:
batch_size = 32
z_dim = 100
learning_rate = 0.0002
beta1 = 0.5


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1

celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
          celeba_dataset.shape, celeba_dataset.image_mode)
(202599, 28, 28, 3)
Epoch 1/1... Discriminator Loss: 5.3640... Generator Loss: 0.0112
Epoch 1/1... Discriminator Loss: 4.3306... Generator Loss: 0.0300
Epoch 1/1... Discriminator Loss: 4.0935... Generator Loss: 0.0569
Epoch 1/1... Discriminator Loss: 3.5543... Generator Loss: 0.1171
Epoch 1/1... Discriminator Loss: 2.7032... Generator Loss: 0.1977
Epoch 1/1... Discriminator Loss: 2.6457... Generator Loss: 0.2551
Epoch 1/1... Discriminator Loss: 2.4295... Generator Loss: 0.3090
Epoch 1/1... Discriminator Loss: 2.5424... Generator Loss: 0.2799
Epoch 1/1... Discriminator Loss: 2.4744... Generator Loss: 0.2918
Epoch 1/1... Discriminator Loss: 2.4670... Generator Loss: 0.3067
Epoch 1/1... Discriminator Loss: 2.1465... Generator Loss: 0.4370
Epoch 1/1... Discriminator Loss: 2.1974... Generator Loss: 0.4549
Epoch 1/1... Discriminator Loss: 2.0738... Generator Loss: 0.4687
Epoch 1/1... Discriminator Loss: 2.0707... Generator Loss: 0.4729
Epoch 1/1... Discriminator Loss: 1.9402... Generator Loss: 0.4823
Epoch 1/1... Discriminator Loss: 1.7790... Generator Loss: 0.5546
Epoch 1/1... Discriminator Loss: 1.6818... Generator Loss: 0.5796
Epoch 1/1... Discriminator Loss: 1.7192... Generator Loss: 0.5455
Epoch 1/1... Discriminator Loss: 1.6930... Generator Loss: 0.6058
Epoch 1/1... Discriminator Loss: 1.6944... Generator Loss: 0.5494
Epoch 1/1... Discriminator Loss: 1.5763... Generator Loss: 0.6451
Epoch 1/1... Discriminator Loss: 1.6474... Generator Loss: 0.6656
Epoch 1/1... Discriminator Loss: 1.6599... Generator Loss: 0.5704
Epoch 1/1... Discriminator Loss: 1.6213... Generator Loss: 0.6267
Epoch 1/1... Discriminator Loss: 1.7350... Generator Loss: 0.5891
Epoch 1/1... Discriminator Loss: 1.5420... Generator Loss: 0.7350
Epoch 1/1... Discriminator Loss: 1.6145... Generator Loss: 0.6690
Epoch 1/1... Discriminator Loss: 1.5641... Generator Loss: 0.5789
Epoch 1/1... Discriminator Loss: 1.6569... Generator Loss: 0.5948
Epoch 1/1... Discriminator Loss: 1.5867... Generator Loss: 0.6599
Epoch 1/1... Discriminator Loss: 1.5837... Generator Loss: 0.6499
Epoch 1/1... Discriminator Loss: 1.5572... Generator Loss: 0.6864
Epoch 1/1... Discriminator Loss: 1.5981... Generator Loss: 0.6602
Epoch 1/1... Discriminator Loss: 1.5111... Generator Loss: 0.7117
Epoch 1/1... Discriminator Loss: 1.4731... Generator Loss: 0.7788
Epoch 1/1... Discriminator Loss: 1.5378... Generator Loss: 0.6289
Epoch 1/1... Discriminator Loss: 1.5119... Generator Loss: 0.7041
Epoch 1/1... Discriminator Loss: 1.4449... Generator Loss: 0.8037
Epoch 1/1... Discriminator Loss: 1.5046... Generator Loss: 0.6791
Epoch 1/1... Discriminator Loss: 1.6331... Generator Loss: 0.6729
Epoch 1/1... Discriminator Loss: 1.4650... Generator Loss: 0.7044
Epoch 1/1... Discriminator Loss: 1.5470... Generator Loss: 0.6666
Epoch 1/1... Discriminator Loss: 1.5641... Generator Loss: 0.7018
Epoch 1/1... Discriminator Loss: 1.4115... Generator Loss: 0.7684
Epoch 1/1... Discriminator Loss: 1.5385... Generator Loss: 0.6633
Epoch 1/1... Discriminator Loss: 1.6549... Generator Loss: 0.6190
Epoch 1/1... Discriminator Loss: 1.6377... Generator Loss: 0.6764
Epoch 1/1... Discriminator Loss: 1.5262... Generator Loss: 0.6726
Epoch 1/1... Discriminator Loss: 1.5803... Generator Loss: 0.6524
Epoch 1/1... Discriminator Loss: 1.5280... Generator Loss: 0.6691
Epoch 1/1... Discriminator Loss: 1.5706... Generator Loss: 0.7014
Epoch 1/1... Discriminator Loss: 1.5802... Generator Loss: 0.6254
Epoch 1/1... Discriminator Loss: 1.4678... Generator Loss: 0.7401
Epoch 1/1... Discriminator Loss: 1.4964... Generator Loss: 0.6974
Epoch 1/1... Discriminator Loss: 1.5405... Generator Loss: 0.6522
Epoch 1/1... Discriminator Loss: 1.5807... Generator Loss: 0.6299
Epoch 1/1... Discriminator Loss: 1.4520... Generator Loss: 0.7578
Epoch 1/1... Discriminator Loss: 1.4105... Generator Loss: 0.8203
Epoch 1/1... Discriminator Loss: 1.4326... Generator Loss: 0.8158
Epoch 1/1... Discriminator Loss: 1.4609... Generator Loss: 0.7105
Epoch 1/1... Discriminator Loss: 1.5252... Generator Loss: 0.7069
Epoch 1/1... Discriminator Loss: 1.4574... Generator Loss: 0.7198
Epoch 1/1... Discriminator Loss: 1.5056... Generator Loss: 0.6709
Epoch 1/1... Discriminator Loss: 1.5667... Generator Loss: 0.6793
Epoch 1/1... Discriminator Loss: 1.6152... Generator Loss: 0.6285
Epoch 1/1... Discriminator Loss: 1.4576... Generator Loss: 0.7157
Epoch 1/1... Discriminator Loss: 1.4615... Generator Loss: 0.7274
Epoch 1/1... Discriminator Loss: 1.4415... Generator Loss: 0.7380
Epoch 1/1... Discriminator Loss: 1.5223... Generator Loss: 0.6949
Epoch 1/1... Discriminator Loss: 1.5230... Generator Loss: 0.6931
Epoch 1/1... Discriminator Loss: 1.5751... Generator Loss: 0.6579
Epoch 1/1... Discriminator Loss: 1.4737... Generator Loss: 0.7356
Epoch 1/1... Discriminator Loss: 1.4981... Generator Loss: 0.6719
Epoch 1/1... Discriminator Loss: 1.4672... Generator Loss: 0.7780
Epoch 1/1... Discriminator Loss: 1.4586... Generator Loss: 0.7883
Epoch 1/1... Discriminator Loss: 1.5164... Generator Loss: 0.6455
Epoch 1/1... Discriminator Loss: 1.5199... Generator Loss: 0.6962
Epoch 1/1... Discriminator Loss: 1.5263... Generator Loss: 0.7175
Epoch 1/1... Discriminator Loss: 1.4558... Generator Loss: 0.7008
Epoch 1/1... Discriminator Loss: 1.5264... Generator Loss: 0.6867
Epoch 1/1... Discriminator Loss: 1.4436... Generator Loss: 0.7830
Epoch 1/1... Discriminator Loss: 1.5298... Generator Loss: 0.6786
Epoch 1/1... Discriminator Loss: 1.5575... Generator Loss: 0.6535
Epoch 1/1... Discriminator Loss: 1.5474... Generator Loss: 0.6511
Epoch 1/1... Discriminator Loss: 1.5291... Generator Loss: 0.6493
Epoch 1/1... Discriminator Loss: 1.5169... Generator Loss: 0.7008
Epoch 1/1... Discriminator Loss: 1.4445... Generator Loss: 0.6943
Epoch 1/1... Discriminator Loss: 1.4275... Generator Loss: 0.7597
Epoch 1/1... Discriminator Loss: 1.5381... Generator Loss: 0.6155
Epoch 1/1... Discriminator Loss: 1.5697... Generator Loss: 0.6414
Epoch 1/1... Discriminator Loss: 1.3719... Generator Loss: 0.7962
Epoch 1/1... Discriminator Loss: 1.5759... Generator Loss: 0.6768
Epoch 1/1... Discriminator Loss: 1.4849... Generator Loss: 0.7302
Epoch 1/1... Discriminator Loss: 1.5131... Generator Loss: 0.7553
Epoch 1/1... Discriminator Loss: 1.3674... Generator Loss: 0.7594
Epoch 1/1... Discriminator Loss: 1.4887... Generator Loss: 0.7298
Epoch 1/1... Discriminator Loss: 1.4974... Generator Loss: 0.7573
Epoch 1/1... Discriminator Loss: 1.5020... Generator Loss: 0.7214
Epoch 1/1... Discriminator Loss: 1.4991... Generator Loss: 0.7085
Epoch 1/1... Discriminator Loss: 1.4694... Generator Loss: 0.7413
Epoch 1/1... Discriminator Loss: 1.4448... Generator Loss: 0.7596
Epoch 1/1... Discriminator Loss: 1.4744... Generator Loss: 0.7242
Epoch 1/1... Discriminator Loss: 1.4285... Generator Loss: 0.7823
Epoch 1/1... Discriminator Loss: 1.3934... Generator Loss: 0.7692
Epoch 1/1... Discriminator Loss: 1.5858... Generator Loss: 0.6051
Epoch 1/1... Discriminator Loss: 1.6972... Generator Loss: 0.7226
Epoch 1/1... Discriminator Loss: 1.5684... Generator Loss: 0.6932
Epoch 1/1... Discriminator Loss: 1.5824... Generator Loss: 0.6127
Epoch 1/1... Discriminator Loss: 1.5488... Generator Loss: 0.7497
Epoch 1/1... Discriminator Loss: 1.5992... Generator Loss: 0.5697
Epoch 1/1... Discriminator Loss: 1.3697... Generator Loss: 0.7561
Epoch 1/1... Discriminator Loss: 1.4518... Generator Loss: 0.8026
Epoch 1/1... Discriminator Loss: 1.5281... Generator Loss: 0.6515
Epoch 1/1... Discriminator Loss: 1.4475... Generator Loss: 0.7449
Epoch 1/1... Discriminator Loss: 1.4868... Generator Loss: 0.6749
Epoch 1/1... Discriminator Loss: 1.5463... Generator Loss: 0.7458
Epoch 1/1... Discriminator Loss: 1.4008... Generator Loss: 0.8164
Epoch 1/1... Discriminator Loss: 1.4743... Generator Loss: 0.7012
Epoch 1/1... Discriminator Loss: 1.4746... Generator Loss: 0.7348
Epoch 1/1... Discriminator Loss: 1.4228... Generator Loss: 0.7554
Epoch 1/1... Discriminator Loss: 1.5363... Generator Loss: 0.6624
Epoch 1/1... Discriminator Loss: 1.4374... Generator Loss: 0.7649
Epoch 1/1... Discriminator Loss: 1.5805... Generator Loss: 0.6415
Epoch 1/1... Discriminator Loss: 1.4639... Generator Loss: 0.7105
Epoch 1/1... Discriminator Loss: 1.4239... Generator Loss: 0.7609
Epoch 1/1... Discriminator Loss: 1.4999... Generator Loss: 0.7351
Epoch 1/1... Discriminator Loss: 1.5308... Generator Loss: 0.6684
Epoch 1/1... Discriminator Loss: 1.4862... Generator Loss: 0.7234
Epoch 1/1... Discriminator Loss: 1.5376... Generator Loss: 0.7395
Epoch 1/1... Discriminator Loss: 1.3900... Generator Loss: 0.7314
Epoch 1/1... Discriminator Loss: 1.4824... Generator Loss: 0.7122
Epoch 1/1... Discriminator Loss: 1.4277... Generator Loss: 0.7303
Epoch 1/1... Discriminator Loss: 1.4876... Generator Loss: 0.7063
Epoch 1/1... Discriminator Loss: 1.4034... Generator Loss: 0.8012
Epoch 1/1... Discriminator Loss: 1.5135... Generator Loss: 0.6872
Epoch 1/1... Discriminator Loss: 1.5278... Generator Loss: 0.6822
Epoch 1/1... Discriminator Loss: 1.5739... Generator Loss: 0.6632
Epoch 1/1... Discriminator Loss: 1.4777... Generator Loss: 0.7048
Epoch 1/1... Discriminator Loss: 1.5269... Generator Loss: 0.6597
Epoch 1/1... Discriminator Loss: 1.4082... Generator Loss: 0.6940
Epoch 1/1... Discriminator Loss: 1.5167... Generator Loss: 0.7117
Epoch 1/1... Discriminator Loss: 1.4022... Generator Loss: 0.7425
Epoch 1/1... Discriminator Loss: 1.4505... Generator Loss: 0.7724
Epoch 1/1... Discriminator Loss: 1.4981... Generator Loss: 0.6652
Epoch 1/1... Discriminator Loss: 1.4605... Generator Loss: 0.7177
Epoch 1/1... Discriminator Loss: 1.3943... Generator Loss: 0.8143
Epoch 1/1... Discriminator Loss: 1.5251... Generator Loss: 0.7227
Epoch 1/1... Discriminator Loss: 1.5336... Generator Loss: 0.6743
Epoch 1/1... Discriminator Loss: 1.4657... Generator Loss: 0.6906
Epoch 1/1... Discriminator Loss: 1.4447... Generator Loss: 0.6636
Epoch 1/1... Discriminator Loss: 1.5261... Generator Loss: 0.6880
Epoch 1/1... Discriminator Loss: 1.4749... Generator Loss: 0.6816
Epoch 1/1... Discriminator Loss: 1.4884... Generator Loss: 0.6764
Epoch 1/1... Discriminator Loss: 1.5818... Generator Loss: 0.6861
Epoch 1/1... Discriminator Loss: 1.3623... Generator Loss: 0.8293
Epoch 1/1... Discriminator Loss: 1.4597... Generator Loss: 0.7257
Epoch 1/1... Discriminator Loss: 1.4875... Generator Loss: 0.7114
Epoch 1/1... Discriminator Loss: 1.4921... Generator Loss: 0.6714
Epoch 1/1... Discriminator Loss: 1.4046... Generator Loss: 0.7483
Epoch 1/1... Discriminator Loss: 1.4224... Generator Loss: 0.7588
Epoch 1/1... Discriminator Loss: 1.5319... Generator Loss: 0.7068
Epoch 1/1... Discriminator Loss: 1.4905... Generator Loss: 0.7577
Epoch 1/1... Discriminator Loss: 1.4179... Generator Loss: 0.8100
Epoch 1/1... Discriminator Loss: 1.4115... Generator Loss: 0.8009
Epoch 1/1... Discriminator Loss: 1.5278... Generator Loss: 0.7264
Epoch 1/1... Discriminator Loss: 1.4665... Generator Loss: 0.7457
Epoch 1/1... Discriminator Loss: 1.4025... Generator Loss: 0.7596
Epoch 1/1... Discriminator Loss: 1.4431... Generator Loss: 0.7067
Epoch 1/1... Discriminator Loss: 1.4611... Generator Loss: 0.6800
Epoch 1/1... Discriminator Loss: 1.3643... Generator Loss: 0.7925
Epoch 1/1... Discriminator Loss: 1.4676... Generator Loss: 0.7568
Epoch 1/1... Discriminator Loss: 1.4247... Generator Loss: 0.7458
Epoch 1/1... Discriminator Loss: 1.5402... Generator Loss: 0.6838
Epoch 1/1... Discriminator Loss: 1.4225... Generator Loss: 0.7323
Epoch 1/1... Discriminator Loss: 1.4212... Generator Loss: 0.7091
Epoch 1/1... Discriminator Loss: 1.4013... Generator Loss: 0.7650
Epoch 1/1... Discriminator Loss: 1.6124... Generator Loss: 0.6126
Epoch 1/1... Discriminator Loss: 1.4413... Generator Loss: 0.7275
Epoch 1/1... Discriminator Loss: 1.4175... Generator Loss: 0.7827
Epoch 1/1... Discriminator Loss: 1.5313... Generator Loss: 0.7015
Epoch 1/1... Discriminator Loss: 1.4733... Generator Loss: 0.7437
Epoch 1/1... Discriminator Loss: 1.5380... Generator Loss: 0.6566
Epoch 1/1... Discriminator Loss: 1.4885... Generator Loss: 0.6703
Epoch 1/1... Discriminator Loss: 1.4298... Generator Loss: 0.7722
Epoch 1/1... Discriminator Loss: 1.5387... Generator Loss: 0.6997
Epoch 1/1... Discriminator Loss: 1.4475... Generator Loss: 0.7757
Epoch 1/1... Discriminator Loss: 1.6006... Generator Loss: 0.5763
Epoch 1/1... Discriminator Loss: 1.4263... Generator Loss: 0.7492
Epoch 1/1... Discriminator Loss: 1.4002... Generator Loss: 0.7488
Epoch 1/1... Discriminator Loss: 1.4202... Generator Loss: 0.7551
Epoch 1/1... Discriminator Loss: 1.5080... Generator Loss: 0.6663
Epoch 1/1... Discriminator Loss: 1.4162... Generator Loss: 0.7423
Epoch 1/1... Discriminator Loss: 1.5071... Generator Loss: 0.7044
Epoch 1/1... Discriminator Loss: 1.4759... Generator Loss: 0.7672
Epoch 1/1... Discriminator Loss: 1.4596... Generator Loss: 0.7542
Epoch 1/1... Discriminator Loss: 1.6015... Generator Loss: 0.6388
Epoch 1/1... Discriminator Loss: 1.4560... Generator Loss: 0.8251
Epoch 1/1... Discriminator Loss: 1.4389... Generator Loss: 0.7278
Epoch 1/1... Discriminator Loss: 1.5643... Generator Loss: 0.6247
Epoch 1/1... Discriminator Loss: 1.4703... Generator Loss: 0.6834
Epoch 1/1... Discriminator Loss: 1.4594... Generator Loss: 0.7296
Epoch 1/1... Discriminator Loss: 1.5398... Generator Loss: 0.6606
Epoch 1/1... Discriminator Loss: 1.3999... Generator Loss: 0.7682
Epoch 1/1... Discriminator Loss: 1.5331... Generator Loss: 0.7610
Epoch 1/1... Discriminator Loss: 1.4676... Generator Loss: 0.7157
Epoch 1/1... Discriminator Loss: 1.5859... Generator Loss: 0.6421
Epoch 1/1... Discriminator Loss: 1.5096... Generator Loss: 0.6698
Epoch 1/1... Discriminator Loss: 1.3937... Generator Loss: 0.7457
Epoch 1/1... Discriminator Loss: 1.5461... Generator Loss: 0.6844
Epoch 1/1... Discriminator Loss: 1.4090... Generator Loss: 0.7475
Epoch 1/1... Discriminator Loss: 1.4243... Generator Loss: 0.7564
Epoch 1/1... Discriminator Loss: 1.4124... Generator Loss: 0.8424
Epoch 1/1... Discriminator Loss: 1.4981... Generator Loss: 0.7306
Epoch 1/1... Discriminator Loss: 1.4198... Generator Loss: 0.7580
Epoch 1/1... Discriminator Loss: 1.5477... Generator Loss: 0.7026
Epoch 1/1... Discriminator Loss: 1.3868... Generator Loss: 0.7507
Epoch 1/1... Discriminator Loss: 1.4136... Generator Loss: 0.8089
Epoch 1/1... Discriminator Loss: 1.4488... Generator Loss: 0.6573
Epoch 1/1... Discriminator Loss: 1.3630... Generator Loss: 0.7980
Epoch 1/1... Discriminator Loss: 1.4666... Generator Loss: 0.7520
Epoch 1/1... Discriminator Loss: 1.4144... Generator Loss: 0.8040
Epoch 1/1... Discriminator Loss: 1.4191... Generator Loss: 0.7106
Epoch 1/1... Discriminator Loss: 1.4551... Generator Loss: 0.7201
Epoch 1/1... Discriminator Loss: 1.4072... Generator Loss: 0.7577
Epoch 1/1... Discriminator Loss: 1.3702... Generator Loss: 0.8429
Epoch 1/1... Discriminator Loss: 1.4127... Generator Loss: 0.8220
Epoch 1/1... Discriminator Loss: 1.4432... Generator Loss: 0.8085
Epoch 1/1... Discriminator Loss: 1.3656... Generator Loss: 0.8028
Epoch 1/1... Discriminator Loss: 1.4220... Generator Loss: 0.7252
Epoch 1/1... Discriminator Loss: 1.4935... Generator Loss: 0.7309
Epoch 1/1... Discriminator Loss: 1.4067... Generator Loss: 0.7766
Epoch 1/1... Discriminator Loss: 1.5067... Generator Loss: 0.7069
Epoch 1/1... Discriminator Loss: 1.4433... Generator Loss: 0.7031
Epoch 1/1... Discriminator Loss: 1.4207... Generator Loss: 0.7810
Epoch 1/1... Discriminator Loss: 1.4906... Generator Loss: 0.6428
Epoch 1/1... Discriminator Loss: 1.4197... Generator Loss: 0.7400
Epoch 1/1... Discriminator Loss: 1.4489... Generator Loss: 0.7812
Epoch 1/1... Discriminator Loss: 1.5083... Generator Loss: 0.7316
Epoch 1/1... Discriminator Loss: 1.4376... Generator Loss: 0.7637
Epoch 1/1... Discriminator Loss: 1.4182... Generator Loss: 0.8302
Epoch 1/1... Discriminator Loss: 1.4277... Generator Loss: 0.7822
Epoch 1/1... Discriminator Loss: 1.3611... Generator Loss: 0.7801
Epoch 1/1... Discriminator Loss: 1.4790... Generator Loss: 0.7140
Epoch 1/1... Discriminator Loss: 1.3511... Generator Loss: 0.7748
Epoch 1/1... Discriminator Loss: 1.5490... Generator Loss: 0.6648
Epoch 1/1... Discriminator Loss: 1.5625... Generator Loss: 0.6632
Epoch 1/1... Discriminator Loss: 1.3552... Generator Loss: 0.7902
Epoch 1/1... Discriminator Loss: 1.4688... Generator Loss: 0.7327
Epoch 1/1... Discriminator Loss: 1.4648... Generator Loss: 0.7075
Epoch 1/1... Discriminator Loss: 1.4231... Generator Loss: 0.7773
Epoch 1/1... Discriminator Loss: 1.5338... Generator Loss: 0.6947
Epoch 1/1... Discriminator Loss: 1.4569... Generator Loss: 0.7036
Epoch 1/1... Discriminator Loss: 1.3966... Generator Loss: 0.8260
Epoch 1/1... Discriminator Loss: 1.4028... Generator Loss: 0.6947
Epoch 1/1... Discriminator Loss: 1.3958... Generator Loss: 0.7623
Epoch 1/1... Discriminator Loss: 1.4442... Generator Loss: 0.7413
Epoch 1/1... Discriminator Loss: 1.4409... Generator Loss: 0.7595
Epoch 1/1... Discriminator Loss: 1.3860... Generator Loss: 0.7638
Epoch 1/1... Discriminator Loss: 1.4577... Generator Loss: 0.7814
Epoch 1/1... Discriminator Loss: 1.4670... Generator Loss: 0.6806
Epoch 1/1... Discriminator Loss: 1.4963... Generator Loss: 0.6693
Epoch 1/1... Discriminator Loss: 1.5198... Generator Loss: 0.6390
Epoch 1/1... Discriminator Loss: 1.4669... Generator Loss: 0.8128
Epoch 1/1... Discriminator Loss: 1.5524... Generator Loss: 0.6497
Epoch 1/1... Discriminator Loss: 1.4288... Generator Loss: 0.7790
Epoch 1/1... Discriminator Loss: 1.3956... Generator Loss: 0.7490
Epoch 1/1... Discriminator Loss: 1.5566... Generator Loss: 0.7022
Epoch 1/1... Discriminator Loss: 1.4786... Generator Loss: 0.7392
Epoch 1/1... Discriminator Loss: 1.4766... Generator Loss: 0.7700
Epoch 1/1... Discriminator Loss: 1.5477... Generator Loss: 0.6462
Epoch 1/1... Discriminator Loss: 1.3831... Generator Loss: 0.7990
Epoch 1/1... Discriminator Loss: 1.4449... Generator Loss: 0.6994
Epoch 1/1... Discriminator Loss: 1.4163... Generator Loss: 0.7517
Epoch 1/1... Discriminator Loss: 1.4528... Generator Loss: 0.7964
Epoch 1/1... Discriminator Loss: 1.4441... Generator Loss: 0.7533
Epoch 1/1... Discriminator Loss: 1.4247... Generator Loss: 0.7422
Epoch 1/1... Discriminator Loss: 1.4865... Generator Loss: 0.7700
Epoch 1/1... Discriminator Loss: 1.3966... Generator Loss: 0.7194
Epoch 1/1... Discriminator Loss: 1.4013... Generator Loss: 0.7678
Epoch 1/1... Discriminator Loss: 1.3739... Generator Loss: 0.8174
Epoch 1/1... Discriminator Loss: 1.3861... Generator Loss: 0.7751
Epoch 1/1... Discriminator Loss: 1.4326... Generator Loss: 0.7274
Epoch 1/1... Discriminator Loss: 1.4046... Generator Loss: 0.8039
Epoch 1/1... Discriminator Loss: 1.4303... Generator Loss: 0.7206
Epoch 1/1... Discriminator Loss: 1.4729... Generator Loss: 0.7364
Epoch 1/1... Discriminator Loss: 1.3982... Generator Loss: 0.7259
Epoch 1/1... Discriminator Loss: 1.4476... Generator Loss: 0.7744
Epoch 1/1... Discriminator Loss: 1.4174... Generator Loss: 0.7977
Epoch 1/1... Discriminator Loss: 1.4444... Generator Loss: 0.6602
Epoch 1/1... Discriminator Loss: 1.4487... Generator Loss: 0.8584
Epoch 1/1... Discriminator Loss: 1.5005... Generator Loss: 0.7724
Epoch 1/1... Discriminator Loss: 1.4889... Generator Loss: 0.6608
Epoch 1/1... Discriminator Loss: 1.4970... Generator Loss: 0.7648
Epoch 1/1... Discriminator Loss: 1.3916... Generator Loss: 0.7475
Epoch 1/1... Discriminator Loss: 1.4395... Generator Loss: 0.7470
Epoch 1/1... Discriminator Loss: 1.4384... Generator Loss: 0.7434
Epoch 1/1... Discriminator Loss: 1.3772... Generator Loss: 0.7912
Epoch 1/1... Discriminator Loss: 1.4495... Generator Loss: 0.7208
Epoch 1/1... Discriminator Loss: 1.3811... Generator Loss: 0.7862
Epoch 1/1... Discriminator Loss: 1.4233... Generator Loss: 0.7489
Epoch 1/1... Discriminator Loss: 1.4798... Generator Loss: 0.7499
Epoch 1/1... Discriminator Loss: 1.4225... Generator Loss: 0.7427
Epoch 1/1... Discriminator Loss: 1.4676... Generator Loss: 0.6884
Epoch 1/1... Discriminator Loss: 1.5433... Generator Loss: 0.6883
Epoch 1/1... Discriminator Loss: 1.6023... Generator Loss: 0.6149
Epoch 1/1... Discriminator Loss: 1.4498... Generator Loss: 0.7815
Epoch 1/1... Discriminator Loss: 1.5295... Generator Loss: 0.6857
Epoch 1/1... Discriminator Loss: 1.4000... Generator Loss: 0.7829
Epoch 1/1... Discriminator Loss: 1.4742... Generator Loss: 0.7613
Epoch 1/1... Discriminator Loss: 1.5021... Generator Loss: 0.7295
Epoch 1/1... Discriminator Loss: 1.4259... Generator Loss: 0.7503
Epoch 1/1... Discriminator Loss: 1.4131... Generator Loss: 0.7575
Epoch 1/1... Discriminator Loss: 1.3962... Generator Loss: 0.8035
Epoch 1/1... Discriminator Loss: 1.4650... Generator Loss: 0.7248
Epoch 1/1... Discriminator Loss: 1.4019... Generator Loss: 0.7885
Epoch 1/1... Discriminator Loss: 1.5032... Generator Loss: 0.7101
Epoch 1/1... Discriminator Loss: 1.4423... Generator Loss: 0.7620
Epoch 1/1... Discriminator Loss: 1.4137... Generator Loss: 0.7878
Epoch 1/1... Discriminator Loss: 1.4866... Generator Loss: 0.7355
Epoch 1/1... Discriminator Loss: 1.4130... Generator Loss: 0.7902
Epoch 1/1... Discriminator Loss: 1.4531... Generator Loss: 0.7161
Epoch 1/1... Discriminator Loss: 1.4559... Generator Loss: 0.7498
Epoch 1/1... Discriminator Loss: 1.4211... Generator Loss: 0.7686
Epoch 1/1... Discriminator Loss: 1.4770... Generator Loss: 0.7422
Epoch 1/1... Discriminator Loss: 1.4300... Generator Loss: 0.7512
Epoch 1/1... Discriminator Loss: 1.4937... Generator Loss: 0.7508
Epoch 1/1... Discriminator Loss: 1.3941... Generator Loss: 0.7898
Epoch 1/1... Discriminator Loss: 1.3981... Generator Loss: 0.7182
Epoch 1/1... Discriminator Loss: 1.3982... Generator Loss: 0.7950
Epoch 1/1... Discriminator Loss: 1.4869... Generator Loss: 0.6797
Epoch 1/1... Discriminator Loss: 1.3928... Generator Loss: 0.7346
Epoch 1/1... Discriminator Loss: 1.4662... Generator Loss: 0.7589
Epoch 1/1... Discriminator Loss: 1.3832... Generator Loss: 0.7815
Epoch 1/1... Discriminator Loss: 1.4216... Generator Loss: 0.7117
Epoch 1/1... Discriminator Loss: 1.4631... Generator Loss: 0.7142
Epoch 1/1... Discriminator Loss: 1.4909... Generator Loss: 0.7579
Epoch 1/1... Discriminator Loss: 1.4226... Generator Loss: 0.7299
Epoch 1/1... Discriminator Loss: 1.4389... Generator Loss: 0.8182
Epoch 1/1... Discriminator Loss: 1.4021... Generator Loss: 0.7450
Epoch 1/1... Discriminator Loss: 1.4735... Generator Loss: 0.7408
Epoch 1/1... Discriminator Loss: 1.4231... Generator Loss: 0.7365
Epoch 1/1... Discriminator Loss: 1.4646... Generator Loss: 0.8127
Epoch 1/1... Discriminator Loss: 1.4037... Generator Loss: 0.7390
Epoch 1/1... Discriminator Loss: 1.4605... Generator Loss: 0.7079
Epoch 1/1... Discriminator Loss: 1.3818... Generator Loss: 0.7674
Epoch 1/1... Discriminator Loss: 1.4341... Generator Loss: 0.8087
Epoch 1/1... Discriminator Loss: 1.3620... Generator Loss: 0.7933
Epoch 1/1... Discriminator Loss: 1.4477... Generator Loss: 0.7466
Epoch 1/1... Discriminator Loss: 1.4778... Generator Loss: 0.7133
Epoch 1/1... Discriminator Loss: 1.3979... Generator Loss: 0.7451
Epoch 1/1... Discriminator Loss: 1.3784... Generator Loss: 0.7109
Epoch 1/1... Discriminator Loss: 1.4306... Generator Loss: 0.7251
Epoch 1/1... Discriminator Loss: 1.4186... Generator Loss: 0.8169
Epoch 1/1... Discriminator Loss: 1.4199... Generator Loss: 0.7496
Epoch 1/1... Discriminator Loss: 1.5130... Generator Loss: 0.6785
Epoch 1/1... Discriminator Loss: 1.3876... Generator Loss: 0.7803
Epoch 1/1... Discriminator Loss: 1.4282... Generator Loss: 0.8118
Epoch 1/1... Discriminator Loss: 1.3616... Generator Loss: 0.7872
Epoch 1/1... Discriminator Loss: 1.4891... Generator Loss: 0.7174
Epoch 1/1... Discriminator Loss: 1.4574... Generator Loss: 0.6982
Epoch 1/1... Discriminator Loss: 1.4022... Generator Loss: 0.7786
Epoch 1/1... Discriminator Loss: 1.5485... Generator Loss: 0.6999
Epoch 1/1... Discriminator Loss: 1.4886... Generator Loss: 0.7262
Epoch 1/1... Discriminator Loss: 1.4306... Generator Loss: 0.6938
Epoch 1/1... Discriminator Loss: 1.4136... Generator Loss: 0.7472
Epoch 1/1... Discriminator Loss: 1.4156... Generator Loss: 0.7105
Epoch 1/1... Discriminator Loss: 1.4531... Generator Loss: 0.6915
Epoch 1/1... Discriminator Loss: 1.4583... Generator Loss: 0.6884
Epoch 1/1... Discriminator Loss: 1.4007... Generator Loss: 0.7133
Epoch 1/1... Discriminator Loss: 1.5402... Generator Loss: 0.6983
Epoch 1/1... Discriminator Loss: 1.4526... Generator Loss: 0.7566
Epoch 1/1... Discriminator Loss: 1.4499... Generator Loss: 0.7163
Epoch 1/1... Discriminator Loss: 1.4316... Generator Loss: 0.7499
Epoch 1/1... Discriminator Loss: 1.4575... Generator Loss: 0.7278
Epoch 1/1... Discriminator Loss: 1.4480... Generator Loss: 0.6951
Epoch 1/1... Discriminator Loss: 1.5132... Generator Loss: 0.6509
Epoch 1/1... Discriminator Loss: 1.4166... Generator Loss: 0.8187
Epoch 1/1... Discriminator Loss: 1.4800... Generator Loss: 0.7050
Epoch 1/1... Discriminator Loss: 1.4676... Generator Loss: 0.7710
Epoch 1/1... Discriminator Loss: 1.4451... Generator Loss: 0.7134
Epoch 1/1... Discriminator Loss: 1.4542... Generator Loss: 0.7478
Epoch 1/1... Discriminator Loss: 1.5013... Generator Loss: 0.7126
Epoch 1/1... Discriminator Loss: 1.5395... Generator Loss: 0.7108
Epoch 1/1... Discriminator Loss: 1.5070... Generator Loss: 0.7052
Epoch 1/1... Discriminator Loss: 1.4277... Generator Loss: 0.7781
Epoch 1/1... Discriminator Loss: 1.6039... Generator Loss: 0.6397
Epoch 1/1... Discriminator Loss: 1.4706... Generator Loss: 0.8217
Epoch 1/1... Discriminator Loss: 1.4737... Generator Loss: 0.7528
Epoch 1/1... Discriminator Loss: 1.3799... Generator Loss: 0.7233
Epoch 1/1... Discriminator Loss: 1.4720... Generator Loss: 0.7392
Epoch 1/1... Discriminator Loss: 1.3869... Generator Loss: 0.7086
Epoch 1/1... Discriminator Loss: 1.4347... Generator Loss: 0.7253
Epoch 1/1... Discriminator Loss: 1.4275... Generator Loss: 0.7278
Epoch 1/1... Discriminator Loss: 1.3811... Generator Loss: 0.7808
Epoch 1/1... Discriminator Loss: 1.3990... Generator Loss: 0.7982
Epoch 1/1... Discriminator Loss: 1.3957... Generator Loss: 0.7940
Epoch 1/1... Discriminator Loss: 1.4187... Generator Loss: 0.7953
Epoch 1/1... Discriminator Loss: 1.4179... Generator Loss: 0.7395
Epoch 1/1... Discriminator Loss: 1.4252... Generator Loss: 0.7679
Epoch 1/1... Discriminator Loss: 1.3753... Generator Loss: 0.7180
Epoch 1/1... Discriminator Loss: 1.4119... Generator Loss: 0.7018
Epoch 1/1... Discriminator Loss: 1.4492... Generator Loss: 0.7468
Epoch 1/1... Discriminator Loss: 1.4848... Generator Loss: 0.7070
Epoch 1/1... Discriminator Loss: 1.3692... Generator Loss: 0.7921
Epoch 1/1... Discriminator Loss: 1.3959... Generator Loss: 0.8155
Epoch 1/1... Discriminator Loss: 1.4834... Generator Loss: 0.7233
Epoch 1/1... Discriminator Loss: 1.3845... Generator Loss: 0.7409
Epoch 1/1... Discriminator Loss: 1.4147... Generator Loss: 0.7511
Epoch 1/1... Discriminator Loss: 1.4392... Generator Loss: 0.7122
Epoch 1/1... Discriminator Loss: 1.4304... Generator Loss: 0.7876
Epoch 1/1... Discriminator Loss: 1.3984... Generator Loss: 0.8000
Epoch 1/1... Discriminator Loss: 1.4349... Generator Loss: 0.7241
Epoch 1/1... Discriminator Loss: 1.4590... Generator Loss: 0.6755
Epoch 1/1... Discriminator Loss: 1.4555... Generator Loss: 0.7148
Epoch 1/1... Discriminator Loss: 1.4240... Generator Loss: 0.7617
Epoch 1/1... Discriminator Loss: 1.4442... Generator Loss: 0.7785
Epoch 1/1... Discriminator Loss: 1.3972... Generator Loss: 0.7584
Epoch 1/1... Discriminator Loss: 1.4622... Generator Loss: 0.7476
Epoch 1/1... Discriminator Loss: 1.4003... Generator Loss: 0.7193
Epoch 1/1... Discriminator Loss: 1.3889... Generator Loss: 0.8194
Epoch 1/1... Discriminator Loss: 1.4368... Generator Loss: 0.6913
Epoch 1/1... Discriminator Loss: 1.4951... Generator Loss: 0.7245
Epoch 1/1... Discriminator Loss: 1.4270... Generator Loss: 0.7721
Epoch 1/1... Discriminator Loss: 1.4297... Generator Loss: 0.7469
Epoch 1/1... Discriminator Loss: 1.3763... Generator Loss: 0.8522
Epoch 1/1... Discriminator Loss: 1.4189... Generator Loss: 0.7415
Epoch 1/1... Discriminator Loss: 1.5181... Generator Loss: 0.7273
Epoch 1/1... Discriminator Loss: 1.4464... Generator Loss: 0.7025
Epoch 1/1... Discriminator Loss: 1.4452... Generator Loss: 0.7763
Epoch 1/1... Discriminator Loss: 1.4505... Generator Loss: 0.7829
Epoch 1/1... Discriminator Loss: 1.5398... Generator Loss: 0.6442
Epoch 1/1... Discriminator Loss: 1.4561... Generator Loss: 0.7094
Epoch 1/1... Discriminator Loss: 1.4257... Generator Loss: 0.8241
Epoch 1/1... Discriminator Loss: 1.4073... Generator Loss: 0.7007
Epoch 1/1... Discriminator Loss: 1.3515... Generator Loss: 0.7941
Epoch 1/1... Discriminator Loss: 1.4705... Generator Loss: 0.7930
Epoch 1/1... Discriminator Loss: 1.3820... Generator Loss: 0.7586
Epoch 1/1... Discriminator Loss: 1.4083... Generator Loss: 0.7538
Epoch 1/1... Discriminator Loss: 1.4111... Generator Loss: 0.7517
Epoch 1/1... Discriminator Loss: 1.4448... Generator Loss: 0.7898
Epoch 1/1... Discriminator Loss: 1.4334... Generator Loss: 0.7078
Epoch 1/1... Discriminator Loss: 1.5423... Generator Loss: 0.7183
Epoch 1/1... Discriminator Loss: 1.4181... Generator Loss: 0.7493
Epoch 1/1... Discriminator Loss: 1.4155... Generator Loss: 0.7471
Epoch 1/1... Discriminator Loss: 1.4670... Generator Loss: 0.7850
Epoch 1/1... Discriminator Loss: 1.3976... Generator Loss: 0.7384
Epoch 1/1... Discriminator Loss: 1.4878... Generator Loss: 0.6749
Epoch 1/1... Discriminator Loss: 1.4222... Generator Loss: 0.7351
Epoch 1/1... Discriminator Loss: 1.3909... Generator Loss: 0.9011
Epoch 1/1... Discriminator Loss: 1.4239... Generator Loss: 0.7589
Epoch 1/1... Discriminator Loss: 1.5134... Generator Loss: 0.7383
Epoch 1/1... Discriminator Loss: 1.4243... Generator Loss: 0.6952
Epoch 1/1... Discriminator Loss: 1.4069... Generator Loss: 0.7975
Epoch 1/1... Discriminator Loss: 1.4724... Generator Loss: 0.7452
Epoch 1/1... Discriminator Loss: 1.4138... Generator Loss: 0.7530
Epoch 1/1... Discriminator Loss: 1.5001... Generator Loss: 0.7467
Epoch 1/1... Discriminator Loss: 1.4635... Generator Loss: 0.6495
Epoch 1/1... Discriminator Loss: 1.3879... Generator Loss: 0.7554
Epoch 1/1... Discriminator Loss: 1.4873... Generator Loss: 0.7470
Epoch 1/1... Discriminator Loss: 1.3267... Generator Loss: 0.8016
Epoch 1/1... Discriminator Loss: 1.4890... Generator Loss: 0.6335
Epoch 1/1... Discriminator Loss: 1.4241... Generator Loss: 0.7446
Epoch 1/1... Discriminator Loss: 1.3620... Generator Loss: 0.7886
Epoch 1/1... Discriminator Loss: 1.4304... Generator Loss: 0.8001
Epoch 1/1... Discriminator Loss: 1.4245... Generator Loss: 0.7123
Epoch 1/1... Discriminator Loss: 1.3895... Generator Loss: 0.7352
Epoch 1/1... Discriminator Loss: 1.4627... Generator Loss: 0.7104
Epoch 1/1... Discriminator Loss: 1.4447... Generator Loss: 0.7608
Epoch 1/1... Discriminator Loss: 1.3661... Generator Loss: 0.7795
Epoch 1/1... Discriminator Loss: 1.4700... Generator Loss: 0.7079
Epoch 1/1... Discriminator Loss: 1.4674... Generator Loss: 0.7616
Epoch 1/1... Discriminator Loss: 1.3764... Generator Loss: 0.7616
Epoch 1/1... Discriminator Loss: 1.4471... Generator Loss: 0.7197
Epoch 1/1... Discriminator Loss: 1.4350... Generator Loss: 0.8078
Epoch 1/1... Discriminator Loss: 1.5185... Generator Loss: 0.6526
Epoch 1/1... Discriminator Loss: 1.4270... Generator Loss: 0.7303
Epoch 1/1... Discriminator Loss: 1.3990... Generator Loss: 0.7486
Epoch 1/1... Discriminator Loss: 1.4316... Generator Loss: 0.7699
Epoch 1/1... Discriminator Loss: 1.4078... Generator Loss: 0.7178
Epoch 1/1... Discriminator Loss: 1.5165... Generator Loss: 0.6994
Epoch 1/1... Discriminator Loss: 1.4944... Generator Loss: 0.7967
Epoch 1/1... Discriminator Loss: 1.4367... Generator Loss: 0.7211
Epoch 1/1... Discriminator Loss: 1.4193... Generator Loss: 0.7894
Epoch 1/1... Discriminator Loss: 1.4829... Generator Loss: 0.7296
Epoch 1/1... Discriminator Loss: 1.4937... Generator Loss: 0.6720
Epoch 1/1... Discriminator Loss: 1.4248... Generator Loss: 0.7370
Epoch 1/1... Discriminator Loss: 1.5123... Generator Loss: 0.6891
Epoch 1/1... Discriminator Loss: 1.4853... Generator Loss: 0.7667
Epoch 1/1... Discriminator Loss: 1.4034... Generator Loss: 0.7170
Epoch 1/1... Discriminator Loss: 1.4340... Generator Loss: 0.7666
Epoch 1/1... Discriminator Loss: 1.3819... Generator Loss: 0.7223
Epoch 1/1... Discriminator Loss: 1.3999... Generator Loss: 0.7822
Epoch 1/1... Discriminator Loss: 1.4754... Generator Loss: 0.7425
Epoch 1/1... Discriminator Loss: 1.4034... Generator Loss: 0.7484
Epoch 1/1... Discriminator Loss: 1.4714... Generator Loss: 0.7327
Epoch 1/1... Discriminator Loss: 1.4913... Generator Loss: 0.6714
Epoch 1/1... Discriminator Loss: 1.4152... Generator Loss: 0.6960
Epoch 1/1... Discriminator Loss: 1.3693... Generator Loss: 0.8862
Epoch 1/1... Discriminator Loss: 1.3978... Generator Loss: 0.7715
Epoch 1/1... Discriminator Loss: 1.4299... Generator Loss: 0.7522
Epoch 1/1... Discriminator Loss: 1.4973... Generator Loss: 0.8238
Epoch 1/1... Discriminator Loss: 1.3799... Generator Loss: 0.8269
Epoch 1/1... Discriminator Loss: 1.4608... Generator Loss: 0.7334
Epoch 1/1... Discriminator Loss: 1.4765... Generator Loss: 0.7651
Epoch 1/1... Discriminator Loss: 1.4531... Generator Loss: 0.7435
Epoch 1/1... Discriminator Loss: 1.4734... Generator Loss: 0.7645
Epoch 1/1... Discriminator Loss: 1.4276... Generator Loss: 0.7928
Epoch 1/1... Discriminator Loss: 1.4276... Generator Loss: 0.7034
Epoch 1/1... Discriminator Loss: 1.3771... Generator Loss: 0.7722
Epoch 1/1... Discriminator Loss: 1.5087... Generator Loss: 0.7648
Epoch 1/1... Discriminator Loss: 1.4564... Generator Loss: 0.7695
Epoch 1/1... Discriminator Loss: 1.4129... Generator Loss: 0.7513
Epoch 1/1... Discriminator Loss: 1.4577... Generator Loss: 0.7951
Epoch 1/1... Discriminator Loss: 1.4389... Generator Loss: 0.7460
Epoch 1/1... Discriminator Loss: 1.4421... Generator Loss: 0.7544
Epoch 1/1... Discriminator Loss: 1.3814... Generator Loss: 0.8242
Epoch 1/1... Discriminator Loss: 1.4487... Generator Loss: 0.6963
Epoch 1/1... Discriminator Loss: 1.4515... Generator Loss: 0.7135
Epoch 1/1... Discriminator Loss: 1.3951... Generator Loss: 0.7510
Epoch 1/1... Discriminator Loss: 1.5154... Generator Loss: 0.6650
Epoch 1/1... Discriminator Loss: 1.4305... Generator Loss: 0.7270
Epoch 1/1... Discriminator Loss: 1.4500... Generator Loss: 0.7172
Epoch 1/1... Discriminator Loss: 1.3783... Generator Loss: 0.7646
Epoch 1/1... Discriminator Loss: 1.3851... Generator Loss: 0.7355
Epoch 1/1... Discriminator Loss: 1.3966... Generator Loss: 0.8641
Epoch 1/1... Discriminator Loss: 1.4060... Generator Loss: 0.8090
Epoch 1/1... Discriminator Loss: 1.3833... Generator Loss: 0.7865
Epoch 1/1... Discriminator Loss: 1.4100... Generator Loss: 0.7838
Epoch 1/1... Discriminator Loss: 1.4733... Generator Loss: 0.7542
Epoch 1/1... Discriminator Loss: 1.4295... Generator Loss: 0.7429
Epoch 1/1... Discriminator Loss: 1.4035... Generator Loss: 0.7419
Epoch 1/1... Discriminator Loss: 1.4595... Generator Loss: 0.7505
Epoch 1/1... Discriminator Loss: 1.4454... Generator Loss: 0.7280
Epoch 1/1... Discriminator Loss: 1.5872... Generator Loss: 0.6965
Epoch 1/1... Discriminator Loss: 1.4686... Generator Loss: 0.7266
Epoch 1/1... Discriminator Loss: 1.4099... Generator Loss: 0.7727
Epoch 1/1... Discriminator Loss: 1.4025... Generator Loss: 0.7403
Epoch 1/1... Discriminator Loss: 1.3693... Generator Loss: 0.7944
Epoch 1/1... Discriminator Loss: 1.4769... Generator Loss: 0.6836
Epoch 1/1... Discriminator Loss: 1.4013... Generator Loss: 0.7580
Epoch 1/1... Discriminator Loss: 1.4833... Generator Loss: 0.6715
Epoch 1/1... Discriminator Loss: 1.4284... Generator Loss: 0.7513
Epoch 1/1... Discriminator Loss: 1.3437... Generator Loss: 0.8358
Epoch 1/1... Discriminator Loss: 1.4663... Generator Loss: 0.7205
Epoch 1/1... Discriminator Loss: 1.3922... Generator Loss: 0.7347
Epoch 1/1... Discriminator Loss: 1.3627... Generator Loss: 0.8093
Epoch 1/1... Discriminator Loss: 1.3775... Generator Loss: 0.7279
Epoch 1/1... Discriminator Loss: 1.4681... Generator Loss: 0.6941
Epoch 1/1... Discriminator Loss: 1.3825... Generator Loss: 0.8202
Epoch 1/1... Discriminator Loss: 1.4015... Generator Loss: 0.7627
Epoch 1/1... Discriminator Loss: 1.4354... Generator Loss: 0.7322
Epoch 1/1... Discriminator Loss: 1.3960... Generator Loss: 0.7210
Epoch 1/1... Discriminator Loss: 1.3981... Generator Loss: 0.7914
Epoch 1/1... Discriminator Loss: 1.3815... Generator Loss: 0.8414
Epoch 1/1... Discriminator Loss: 1.3835... Generator Loss: 0.7430
Epoch 1/1... Discriminator Loss: 1.4597... Generator Loss: 0.7055
Epoch 1/1... Discriminator Loss: 1.4145... Generator Loss: 0.8698
Epoch 1/1... Discriminator Loss: 1.3869... Generator Loss: 0.7618
Epoch 1/1... Discriminator Loss: 1.4306... Generator Loss: 0.8205
Epoch 1/1... Discriminator Loss: 1.4270... Generator Loss: 0.8025
Epoch 1/1... Discriminator Loss: 1.4122... Generator Loss: 0.7214
Epoch 1/1... Discriminator Loss: 1.3731... Generator Loss: 0.8750
Epoch 1/1... Discriminator Loss: 1.4057... Generator Loss: 0.6877
Epoch 1/1... Discriminator Loss: 1.4312... Generator Loss: 0.7839
Epoch 1/1... Discriminator Loss: 1.4217... Generator Loss: 0.7472
Epoch 1/1... Discriminator Loss: 1.4058... Generator Loss: 0.7784
Epoch 1/1... Discriminator Loss: 1.3632... Generator Loss: 0.7438
Epoch 1/1... Discriminator Loss: 1.3700... Generator Loss: 0.7978
Epoch 1/1... Discriminator Loss: 1.4421... Generator Loss: 0.7886
Epoch 1/1... Discriminator Loss: 1.4500... Generator Loss: 0.7510
Epoch 1/1... Discriminator Loss: 1.3934... Generator Loss: 0.7676
Epoch 1/1... Discriminator Loss: 1.4489... Generator Loss: 0.7658
Epoch 1/1... Discriminator Loss: 1.4356... Generator Loss: 0.8140
Epoch 1/1... Discriminator Loss: 1.4605... Generator Loss: 0.7319
Epoch 1/1... Discriminator Loss: 1.4547... Generator Loss: 0.7114
Epoch 1/1... Discriminator Loss: 1.4894... Generator Loss: 0.7245
Epoch 1/1... Discriminator Loss: 1.3938... Generator Loss: 0.7840
Epoch 1/1... Discriminator Loss: 1.4571... Generator Loss: 0.7370
Epoch 1/1... Discriminator Loss: 1.4571... Generator Loss: 0.7279
Epoch 1/1... Discriminator Loss: 1.4638... Generator Loss: 0.7201
Epoch 1/1... Discriminator Loss: 1.4291... Generator Loss: 0.7345
Epoch 1/1... Discriminator Loss: 1.4365... Generator Loss: 0.7614
Epoch 1/1... Discriminator Loss: 1.4228... Generator Loss: 0.7351
Epoch 1/1... Discriminator Loss: 1.3994... Generator Loss: 0.7551
Epoch 1/1... Discriminator Loss: 1.4998... Generator Loss: 0.7319
Epoch 1/1... Discriminator Loss: 1.3758... Generator Loss: 0.7822
Epoch 1/1... Discriminator Loss: 1.3998... Generator Loss: 0.7840
Epoch 1/1... Discriminator Loss: 1.4157... Generator Loss: 0.7860
Epoch 1/1... Discriminator Loss: 1.3545... Generator Loss: 0.8838
Epoch 1/1... Discriminator Loss: 1.4784... Generator Loss: 0.6610
Epoch 1/1... Discriminator Loss: 1.3886... Generator Loss: 0.7670
Epoch 1/1... Discriminator Loss: 1.4449... Generator Loss: 0.7126
Epoch 1/1... Discriminator Loss: 1.4405... Generator Loss: 0.7073
Epoch 1/1... Discriminator Loss: 1.3681... Generator Loss: 0.7779
Epoch 1/1... Discriminator Loss: 1.4467... Generator Loss: 0.7534
Epoch 1/1... Discriminator Loss: 1.3360... Generator Loss: 0.8154
Epoch 1/1... Discriminator Loss: 1.4116... Generator Loss: 0.7343
Epoch 1/1... Discriminator Loss: 1.4261... Generator Loss: 0.7425
Epoch 1/1... Discriminator Loss: 1.4344... Generator Loss: 0.7136
Epoch 1/1... Discriminator Loss: 1.4301... Generator Loss: 0.6855
Epoch 1/1... Discriminator Loss: 1.3735... Generator Loss: 0.8635
Epoch 1/1... Discriminator Loss: 1.4239... Generator Loss: 0.7277
Epoch 1/1... Discriminator Loss: 1.4367... Generator Loss: 0.7462
Epoch 1/1... Discriminator Loss: 1.3733... Generator Loss: 0.8073
Epoch 1/1... Discriminator Loss: 1.4099... Generator Loss: 0.7609
Epoch 1/1... Discriminator Loss: 1.4141... Generator Loss: 0.7759
Epoch 1/1... Discriminator Loss: 1.4728... Generator Loss: 0.7388
Epoch 1/1... Discriminator Loss: 1.4317... Generator Loss: 0.7634
Epoch 1/1... Discriminator Loss: 1.3940... Generator Loss: 0.7874
Epoch 1/1... Discriminator Loss: 1.4034... Generator Loss: 0.7583
Epoch 1/1... Discriminator Loss: 1.4079... Generator Loss: 0.7622
Epoch 1/1... Discriminator Loss: 1.3872... Generator Loss: 0.7619
Epoch 1/1... Discriminator Loss: 1.4496... Generator Loss: 0.7578
Epoch 1/1... Discriminator Loss: 1.3834... Generator Loss: 0.7416
Epoch 1/1... Discriminator Loss: 1.4400... Generator Loss: 0.7414
Epoch 1/1... Discriminator Loss: 1.4380... Generator Loss: 0.7591
Epoch 1/1... Discriminator Loss: 1.3991... Generator Loss: 0.7161
Epoch 1/1... Discriminator Loss: 1.3643... Generator Loss: 0.7964
Epoch 1/1... Discriminator Loss: 1.3879... Generator Loss: 0.8296
Epoch 1/1... Discriminator Loss: 1.4453... Generator Loss: 0.7420
Epoch 1/1... Discriminator Loss: 1.4645... Generator Loss: 0.6956
Epoch 1/1... Discriminator Loss: 1.4619... Generator Loss: 0.8050
Epoch 1/1... Discriminator Loss: 1.4042... Generator Loss: 0.7358
Epoch 1/1... Discriminator Loss: 1.4379... Generator Loss: 0.8494
Epoch 1/1... Discriminator Loss: 1.4748... Generator Loss: 0.7080
Epoch 1/1... Discriminator Loss: 1.3940... Generator Loss: 0.7763
Epoch 1/1... Discriminator Loss: 1.3911... Generator Loss: 0.7577
Epoch 1/1... Discriminator Loss: 1.4540... Generator Loss: 0.7335
Epoch 1/1... Discriminator Loss: 1.4149... Generator Loss: 0.8111
Epoch 1/1... Discriminator Loss: 1.4062... Generator Loss: 0.8131
Epoch 1/1... Discriminator Loss: 1.4207... Generator Loss: 0.7172
Epoch 1/1... Discriminator Loss: 1.3879... Generator Loss: 0.7593
Epoch 1/1... Discriminator Loss: 1.3619... Generator Loss: 0.8221

Submitting This Project

When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.